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Researchers at Carnegie Mellon University have developed an efficient new way to quickly analyze complex geometric models by borrowing a computational approach that made photorealistic anima...
We formalize the problem of program verification as a learning problem, showing that invariants in program verification can be regarded as geometric concepts in machine learning. Safety properties de-...
Linear Time Approximation Schemes for Geometric Maximum Coverage
Maximum coverage Geometric set cover Polynomial-time approximation scheme
2016/1/22
We study approximation algorithms for the following geo-metric version of the maximum coverage problem: Let P be a set of n weighted points in the plane. We want to place m a × b rectangles such that ...
A Geometric Framework for Transfer Learning Using Manifold Alignment
Dimensionality Reduction Manifold Alignment Multiscale Analysis Representation Learning Topic Model Transfer Learning
2014/12/18
Many machine learning problems involve dealing with a large amount of high-dimensional data across diverse domains. In addition, annotating or labeling the data is expensive as it involves significant...